Recovery of traffic information through graph signal processing

The generation of data sets from traffic variables within the roads of a city is increasing due to the implementation of sensors, monitoring stations, or more elaborate systems, such as synchronised drones to record the dynamics of a city. However, each method has a limited coverage area and it is necessary to extrapolate the values for the road network. Constructing a road graph of a city, each node represents a road and the edges represent the intersection between two roads. Considering the values of the traffic variables as graph signals, we apply graph signal recovery methods based on distinct notions of smooth graph signals to complete the values on the whole network from the available values on a small subset of nodes. The experimental results on the pNEUMA data set on the Athens road graph show that the recovery methods are a potential solution to completing the traffic status on an urban network. Additionally, as one of the further interpretations that are possible to obtain from a complete graph traffic signal, we use the recovered volume signal to estimate the traffic flows within the area of Athens covered by its road graph through Fick’s law based on the combinatorial Laplacian matrix. We show that the smallest flow values are located in the zones with a higher number of points of interest, and also that residential areas are the main sources and destinations of traffic flows.